{"id":"W4248763964","doi":"10.1515/iupac.79.0962","title":"Bystander Exposure","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Toxicology; Hazard; Computer science; Chemistry; Philosophy; Biology; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001715896,0.001368258,0.001993672,0.003389555,0.000728805,0.002339796,0.002299379,0.001876443,0.1040295],"category_scores_gemma":[0.01569045,0.0004129477,0.002469932,0.004096125,0.00030647,0.001692983,0.001722198,0.0015614,0.05480882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328426,"about_ca_system_score_gemma":0.002165132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01206345,"about_ca_topic_score_gemma":0.01988216,"domain_scores_codex":[0.9975957,0.0003566383,0.0005706291,0.0007798072,0.0005115013,0.0001856879],"domain_scores_gemma":[0.9940031,0.001932857,0.001239031,0.001169953,0.001365688,0.0002894925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006337696,0.00006822983,0.01058653,0.005842195,0.0003257264,0.0000931926,0.00005404923,0.000451855,0.0002072132,0.0009488962,0.9584181,0.02237025],"study_design_scores_gemma":[0.0004603016,0.00007808268,0.02532892,0.00229215,0.0003496368,0.0003582249,0.0001043602,0.0002373163,0.0004352653,0.002180689,0.9681151,0.00005989577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004523729,0.0006372499,0.0001212945,0.0001054862,0.00007071102,0.00005352891,0.9961511,0.0001142329,0.002294069],"genre_scores_gemma":[0.002790764,0.0006951169,0.000470365,0.0003647785,0.00007009453,0.0003698564,0.9908662,0.00006485826,0.004308015],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1040295,"threshold_uncertainty_score":0.3480133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009881274915724802,"score_gpt":0.3427034210599531,"score_spread":0.3328221461442282,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}